Methods for cancer prognosis and diagnosis

ABSTRACT

The invention provides methods for prognosis, diagnosis, staging and disease progression in human cancer patients related to expression levels of a plurality of genes that are differentially expressed in chemotherapeutic drug resistant and drug sensitive tumor cells.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention relates to cancer diagnosis and treatment, and specifically to the determination of a drug resistance phenotype in neoplastic cells from cancer patients. The invention specifically relates to the separation of chemotherapeutic drug resistant neoplastic cells from drug sensitive neoplastic cells and stromal cells. The invention in particular relates to the identification of genes that are differentially expressed in chemotherapeutic drug resistant neoplastic cells compared with the expression of these genes in drug sensitive neoplastic cells. As part of this identification, the invention provides a pattern of expression from a selected number of identified genes, the expression of which is increased or decreased in chemotherapeutic drug resistant neoplastic cells. The invention provides methods for identifying such genes and expression patterns of such genes and using this information to make clinical decisions on cancer treatment, especially chemotherapeutic drug treatment of cancer patients.

2. Summary of the Related Art

Cancer remains one of the leading causes of death in the United States. Clinically, a broad variety of medical approaches, including surgery, radiation therapy and chemotherapeutic drug therapy are currently being used in the treatment of human cancer (see the textbook CANCER: Principles & Practice of Oncology. 2d Edition, De Vita et al., eds., J. B. Lippincott Company, Philadelphia, Pa., 1985). However, it is recognized that such approaches continue to be limited by a fundamental inability to accurately predict the likelihood of clinically successful outcome, particularly with regard to the sensitivity or resistance of a particular patient's tumor to a chemotherapeutic agent or combinations of chemotherapeutic agents.

A broad variety of chemotherapeutic agents are used in the treatment of human cancer. These include the plant alkaloids vincristine, vinblastine, vindesine, and VM-26; the antibiotics actinomycin-D, doxorubicin, daunorubicin, mithramycin, mitomycin C and bleomycin; the antimetabolites methotrexate, 5-fluorouracil, 5-fluorodeoxyuridine, 6-mercaptopurine, 6-thioguanine, cytosine arabinoside, 5-aza-cytidine and hydroxyurea; the alkylating agents cyclophosphamide, melphalan, busulfan, CCNU, MeCCNU, BCNU, streptozotocin, chlorambucil, bis-diamminedichloroplatinum, azetidinylbenzoquinone; and the miscellaneous agents dacarbazine, mAMSA and mitoxantrone (DeVita et al., Id.). However, some neoplastic cells become resistant to specific chemotherapeutic agents, in some instances even to multiple chemotherapeutic agents, and some tumors are intrinsically resistant to certain chemotherapeutic agents. Such drug resistance or multiple drug resistance can theoretically arise from expression of genes that confer resistance to the agent, or from lack of expression of genes that make the cells sensitive to a particular anticancer drug. One example of the former type is the multidrug resistance gene, MDR1, which encodes an integral plasma membrane protein termed P-glycoprotein that is an non-specific, energy-dependent efflux pump. (See Roninson (ed)., 1991, Molecular and Cellular Biology of Multidrug Resistance in Tumor Cells, Plenum Press, N.Y., 1991; Gottesman et al., 1991, in Biochemical Bases for Multidrug Resistance in Cancer, Academic Press, N.Y., Chapter 11 for reviews). Examples of the latter type include topoisomerase II, the expression of which makes cells sensitive to the anticancer drug etoposide. Decreased expression of this enzyme makes neoplastic cells resistant to this drug. (See Gudkov et al., 1993, Proc. Natl. Acad. Sci. USA 90: 3231-3235). Although these are just single examples of the way that modulation of gene expression can influence chemotherapeutic drug sensitivity or resistance in neoplastic cells, these examples demonstrate the diagnostic and prognostic potential for identifying genes the expression of which (or the pattern of gene expression modulation thereof) are involved in mediating the clinical effectiveness of anticancer drug treatment.

Thus, there is a need in this art for developing methods for identifying genes and gene expression patterns that are predictive of the clinical effectiveness of anticancer drug treatment therapies, in order to make more informed decisions for treating individual cancer patients with anticancer drugs having greatest likelihood of producing a positive outcome.

SUMMARY OF THE INVENTION

The present invention provides methods identifying genes and gene expression patterns that are predictive of the clinical effectiveness of anticancer drug treatment therapies.

In a first aspect the invention provides a method for separating living neoplastic cells from dead cells and living stromal cells in a mixed population of cells from a tumor sample, the method comprising the steps of:

-   -   a) contacting the mixed population of cells with a vital stain         or fluorescent dye;     -   b) contacting the mixed population of cells with a         detectably-labeled immunological reagent that specifically binds         to neoplastic cells; and     -   c) selecting the cells in the mixed population of step (b) that         are not stained with the vital stain and that bind the         immunological reagent.         In a preferred embodiment, the vital stain is propidium iodide.         Most preferably, the immunological reagent is a tumor-specific         antibody that is detectably labeled with a fluorescent label and         the cells are separated by fluorescence activated cell sorting.         In certain embodiments, the tumor sample is a solid tumor sample         and the mixed cell population is a disaggregated tumor sample.         In other embodiments, the tumor sample is a hematopoietic tumor         sample and the mixed cell population is a nucleated         hematopoietic cell sample.

In a second aspect, the invention provides a method for separating living neoplastic cells that are resistant to a cytotoxic compound from dead cells, living stromal cells and living neoplastic cells that are sensitive to the cytotoxic compound in a mixed population of cells from a tumor sample, the method comprising the steps of:

-   -   a) contacting the mixed population of cells with the cytotoxic         compound for a time and at a concentration wherein the stromal         cells and neoplastic cells that are sensitive to the cytotoxic         compound undergo apoptosis;     -   b) contacting the mixed population of step (a) with a vital         stain or fluorescent dye;     -   c) contacting the mixed population of cells of step (b) with a         discrimination compound that specifically binds to apoptotic         cells;     -   d) contacting the mixed cell population of step (c) with a         detectably-labeled immunological reagent that specifically binds         to the apoptotic cell discrimination compound; and     -   e) selecting the cells in the mixed population of step (c) that         are not stained with the vital stain and that do not bind the         immunological reagent.         In a preferred embodiment, the vital stain is propidium iodide.         Most preferably, the apoptosis discrimination reagent is Annexin         V and the immunological reagent is an Annexin V-specific         antibody that is detectably labeled with a fluorescent label,         wherein the cells are separated by fluorescence activated cell         sorting. In preferred embodiments, the mixed population is         contacted with the cytotoxic compound under in vitro cell         culture conditions whereby the cells cannot attach to a solid         substrate. In certain embodiments, the tumor sample is a solid         tumor sample and the mixed cell population is a disaggregated         tumor sample. In other embodiments, the tumor sample is a         hematopoietic tumor sample and the mixed cell population is a         nucleated hematopoietic cell sample.

In yet a third aspect, the invention provides a method for detecting a gene expression profile of living neoplastic cells that are resistant to a cytotoxic compound and distinguishing such a profile from the gene expression profile of living neoplastic cells that are sensitive to the cytotoxic compound in a mixed population of cells from a tumor sample, the method comprising the steps of:

-   -   a) contacting the mixed population of cells with the cytotoxic         compound for a time and at a concentration wherein the         neoplastic cells that are sensitive to the cytotoxic compound         undergo apoptosis;     -   b) contacting the mixed population of step (a) with a vital         stain or fluorescent dye;     -   c) contacting the mixed population of cells of step (b) with a         discrimination compound that specifically binds to apoptotic         cells;     -   d) contacting the mixed cell population of step (c) with a         detectably-labeled immunological reagent that specifically binds         to the apoptotic cell discrimination compound; and     -   e) separating the cells in the mixed population of step (d) that         are not stained with the vital stain from the cells that are         stained with the vital stain;     -   f) separating the cells in the mixed population of step (e) that         are not stained with the vital stain and that do not bind the         immunological reagent from the cells in the mixed population of         step (c) that are not stained with the vital stain and that do         bind the immunological reagent;     -   g) isolating cellular RNA from the each of the separated cells         selected in step (f);     -   h) preparing detectably-labeled cDNA from the cellular RNA         isolated in step (g);     -   i) hybridizing each of the cDNA preparations prepared in         step (h) to a gene array comprising at least 4000 eukaryotic         genes;     -   j) detecting a pattern of gene expression for hybridization of         each of the cDNA preparations prepared from the mRNA isolated         from the cells selected in step (f); and     -   k) comparing the pattern of gene expression detected in step (j)         from hybridization of the microarray with cDNA from cells that         are not stained with the vital stain and that do not bind the         immunological reagent with a pattern of gene expression obtained         by hybridizing cDNA prepared from cells that are not stained         with the vital stain and that do bind the immunological reagent.         In a preferred embodiment, the vital stain is propidium iodide.         Most preferably, the apoptosis discrimination reagent is Annexin         V and the immunological reagent is an Annexin V-specific         antibody that is detectably labeled with a fluorescent label,         wherein the cells are separated by fluorescence activated cell         sorting. In preferred embodiments, the mixed population is         contacted with the cytotoxic compound under in vitro cell         culture conditions whereby the cells cannot attach to a solid         substrate. In certain embodiments, the tumor sample is a solid         tumor sample and the mixed cell population is a disaggregated         tumor sample. In other embodiments, the tumor sample is a         hematopoietic tumor sample and the mixed cell population is a         nucleated hematopoietic cell sample.

In another aspect, the invention provides a diagnostic assay for characterizing tumors and neoplastic cells, particularly human neoplastic cells, wherein cytotoxic drug resistant, and most preferably chemotherapeutic drug resistant neoplastic cells, by the differential expression of genes and patterns of genes whereby the drug resistant phenotype is associated with, identified by and can be diagnosed on the basis thereof. This diagnostic assay comprises detecting, qualitatively or preferably quantitatively, the expression levels of a gene or a plurality of genes comprising a pattern of expression of genes and making a diagnosis of drug resistance on the basis of this expression pattern of a gene or plurality of genes. In a preferred embodiment, the invention provides methods for identifying a gene or a plurality of genes showing differential gene expression in drug resistant neoplastic cells. In other preferred embodiments, the invention provides methods for detecting expression of a gene or a plurality of genes comprising a pattern of gene expression in drug resistant neoplastic cells. In still other embodiments, the invention provides these methods for a multiplicity of chemotherapeutic drugs to determine drugs for which a patient's tumor is not resistant or shows a minimal level of resistance.

In another embodiment, the invention provides a starting point for in vitro drug screening and rational design of pharmaceutical products that are more effective antineoplastic agents. By identifying a pattern of differential gene expression related to drug resistance, strategies can be developed for creating pharmaceutical products that are improved chemotherapeutic agents to more effectively treat neoplastic disease.

It is an advantage of the methods of this invention that pure neoplastic cell populations from solid and hematopoietic tumors, both malignant and benign, can be obtained separated from stromal cells, infiltrating non-neoplastic hematopoietic cells and other tumor components. This feature of the inventive methods are advantageous because the presence of such contaminating, non-neoplastic cells in tumor sample preparations confounds analyses directed at detecting neoplastic cell-specific properties, such as patterns of gene expression as disclosed herein. It is also an advantage of the present inventive methods that drug-resistant and drug-sensitive neoplastic cells can be separated from pure neoplastic cell populations. As a result, RNA preparations specific for drug-resistant and drug-sensitive neoplastic cells are obtained that can be used to identify genes, and patterns of genes, that are differentially expressed in drug-resistant and drug-sensitive neoplastic cells. In addition, the methods of the invention as provided permit drug-resistant and drug-sensitive neoplastic cells to be simultaneously treated with cytotoxic drugs in the same mixed cell culture, thereby avoiding experimental variability.

Specific preferred embodiments of the present invention will become evident from the following more detailed description of certain preferred embodiments and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic flowchart illustrating an embodiment of the methods of the invention showing how drug-resistant neoplastic cell-specific mRNA is used to probe a gene expression microarray.

FIGS. 2A through 2C are fluorescence-activated cell sorting (FACS) profiles of SKBR3 cells showing cell scatter (FIG. 2A, left), cell viability (FIG. 2A, right), HER2 antibody binding versus non-specific isotypic antibody binding (FIG. 2B), and a resort of HER2 antibody binding cells sorted as shown in FIG. 2B (FIG. 2C).

FIG. 3 is a graph showing drug sensitivity in a HER2-sorted population of SKBR3 cells as determined by EDR assay and cytophobic culture plate assay.

FIG. 4 is a photograph of an agarose gel electrophoretic analysis of RNA integrity from cytotoxic drug-treated cells. Lane 1 is a blank control; lane 2 is a 100 nucleotide control; lane 3 is RNA from doxorubicin-resistant SKBR3 cells; lane 4 is RNA from doxorubicin-sensitive SKBR3 cells; lane 5 is RNA from doxorubicin-resistant cells; and lane 6 is RNA from doxorubicin-sensitive cells from a human breast tumor sample.

FIGS. 5A through 5D are fluorescence-activated cell sorting (FACS) profiles of cells from SKBR3 cells after in vitro cytotoxic drug treatment. FIG. 5A shows cell scatter in the lower left quadrant, FIG. 5B shows separation into living, drug-resistant neoplastic cells (R2 in the lower left quadrant), apoptotic, drug-sensitive cells (R1 in the lower right quadrant) and dying, drug-sensitive cells (in the upper right quadrant). FIG. 5C provides confirmation of the separation of apoptotic, drug-sensitive cells (the sorted cells resort into the lower right quadrant). FIG. 5D provides confirmation of the separation of living, drug-resistant cells (the sorted cells resort into the lower left quadrant).

FIGS. 6A and 6B are FACS profiles of HER2 antibody binding to SHBR3 cells analyzed after cell culture following separation from non-neoplastic cells by FACS based on anti-HER2 antibody binding. FIG. 6A shows that the majority of the cells remained viable, and FIG. 6B shows that the cells bound HER2.

FIG. 7 is a schematic diagram of the results of a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-resistant SKBR3 cells.

FIG. 8 is a schematic diagram of the results of a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-sensitive SKBR3 cells.

FIG. 9 is a schematic diagram of a comparison of the results of a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-sensitive SKBR3 cells with a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-sensitive SKBR3 cells.

FIGS. 10A through 10D are fluorescence-activated cell sorting (FACS) profiles of cells from a human breast tumor sample. FIG. 10A shows cell viability, FIG. 10B shows negligible non-specific isotypic antibody binding, FIG. 10C shows separation of the population into apoptotic, drug-sensitive neoplastic cells (R2) and living, drug-resistant neoplastic cells (R3). FIG. 10D provides confirmation that 96% of the sorted cells are viable (FIG. 10D, top) and that 97% of the sorted cells were HER2 positive (FIG. 9D, bottom).

FIGS. 11A and 11B are FACS profiles of HER2 antibody binding human breast tumor cells analyzed after cell culture following separation from non-neoplastic cells by FACS based on anti-HER2 antibody binding. FIG. 11A shows that 91.5% of the cells. remained viable, and FIG. 11B shows that 96.2% of the cells bound HER2.

FIGS. 12A through 12D are fluorescence-activated cell sorting (FACS) profiles of cells from a human breast tumor sample after in vitro cytotoxic drug treatment. FIG. 12A shows cell scatter (99.8% in the lower left quadrant), FIG. 12B shows separation into living, drug-resistant neoplastic cells (R2; 14.6% of cells in the lower left quadrant), apoptotic, drug-sensitive cells (R1; 40.5% in the lower right quadrant) and dying, drug-sensitive cells (44.7% in the upper right quadrant). FIG. 12C provides confirmation of the separation of apoptotic, drug-sensitive cells (93.3% of the sorted cells resort into the lower right quadrant). FIG. 12D provides confirmation of the separation of living, drug-resistant cells (92.25% of the sorted cells resort into the lower left quadrant).

FIG. 13 is a schematic diagram of the results of a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-resistant human breast tumor-derived neoplastic cells.

FIG. 14 is a schematic diagram of the results of a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-sensitive human breast tumor-derived neoplastic cells.

FIG. 15 is a schematic diagram of a comparison of the results of a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-sensitive human breast tumor-derived neoplastic cells with a gene expression microarray analysis hybridized with cDNA prepared from doxorubicin-sensitive human breast tumor-derived neoplastic cells.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention provides a method for making a prognosis about disease course in a human cancer patient. For the purposes of this invention, the term “prognosis” is intended to encompass predictions and likelihood analysis of disease progression, particularly tumor recurrence, metastatic spread and disease relapse. The prognostic methods of the invention are intended to be used clinically in making decisions concerning treatment modalities, including therapeutic intervention, diagnostic criteria such as disease staging, and disease monitoring and surveillance for metastasis or recurrence of neoplastic disease.

The methods of the invention are preferably performed using human cancer patient tumor samples, most preferably samples preserved, for example in paraffin, and prepared for histological and immunohistochemical analysis.

For the purposes of this invention, the term “tumor sample” is intended to include resected solid tumors, biopsy material, pathological specimens, bone marrow aspirates, and blood samples comprising neoplastic cells of hematopoietic origin, as well as benign tumors, particularly tumors of certain tissues such as brain and the central nervous system. One of ordinary skill will appreciate that samples derived from solid tumors will require combinations of physical and chemical/enzymatic disaggregation to separate neoplastic cells from stromal cells and infiltrating hematopoietic cells, while hematopoietic tumor samples including leukemias and lymphomas will be obtained as mixed cell populations in blood, serum or plasma, and will require separation from non-neoplastic components thereof, particularly from red blood cells that can be lysed by treatment with hypotonic solutions and from other nucleated cells, whereby separation is achieved by differential centrifugation and other methods known in the art.

Living cells are separated from dying cells, dead cells and cell debris, and drug sensitive and drug resistant cells are separated from each other and from non-neoplastic cells according to the methods of the invention by cell sorting methods, most preferably fluorescence-activated cell sorting (FACS). Separation of living cells from dying cells, dead cells and cell debris is facilitated by contacting mixed cell populations with a vital stain, preferably a fluorescent vital stain, such as propidium iodide (PI) and ethidium bromide (EtBr). Separation of drug sensitive and drug resistant cells from one another and from non-neoplastic cells using reagents, most preferably immunological agents, that discriminate between such cells. In particular, drug resistant neoplastic cells are separated from drug sensitive neoplastic cells after incubation with a cytotoxic amount of a chemotherapeutic drug by contacting the mixed cell population with a discrimination compound that specifically binds to apoptotic cells, and separation is achieved using reagents, most preferably immunological agents, that specifically binds to the discrimination compound. In preferred embodiments, the discrimination compound is an annexin, most preferably annexin V or antibodies directed against caspases.

For the purposes of this invention, the term “immunological reagents” is intended to encompass antisera and antibodies, particularly monoclonal antibodies, as well as fragments thereof (including F(ab), F(ab)₂, F(ab)′ and F_(v) fragments). Also included in the definition of immunological reagent are chimeric antibodies, humanized antibodies, and recombinantly-produced antibodies and fragments thereof, as well as aptamers (i.e., oligonucleotides capable of interacting with target molecules such as peptides). Immunological methods used in conjunction with the reagents of the invention include direct and indirect (for example, sandwich-type) labeling techniques, immunoaffinity columns, immunomagnetic beads, fluorescence activated cell sorting (FACS), enzyme-linked immunosorbent assays (ELISA), and radioimmune assay (RIA), most preferably FACS. For use in these assays, the neoplastic immunological reagents can be labeled, using fluorescence, antigenic, radioisotopic or biotin labels, among others, or a labeled secondary or tertiary immunological detection reagent can be used to detect binding of the neoplastic immunological reagents (i.e., in secondary antibody (sandwich) assays).

Examples of immunological reagents useful in the practice of this invention include antibodies, most preferably monoclonal antibodies, that recognize tumor antigens such as CA15-3 (breast cancer), CA19-9 (gastrointestinal cancer), CA125 (ovarian cancer), CA242 (gastrointestinal cancer), p53 (colorectal cancer), prostate-specific acid phosphatase (prostate cancer), Rb (retinoblastoma), CD56 (small cell lung cancer), prostate-specific antigen (prostate cancer), carcinoembryonic antigen (CEA), melanoma antigen and melanoma-associated antigens (melanoma), mucin-1 (carcinoma), HER2 (breast cancer), and EGFR (breast and ovarian cancer).

The immunological reagents of the invention are preferably detectably-labeled, most preferably using fluorescent labels that have excitation and emission wavelengths adapted for detection using commercially-available instruments such as and most preferably fluorescence activated cell sorters. Examples of fluorescent labels useful in the practice of the invention include phycoerythrin (PE), fluorescein isothiocyanate (FITC), rhodamine (RH), Texas Red (TX), Cy3, Hoechst 33258, and 4′,6-diamidino-2-phenylindole (DAPI). Such labels can be conjugated to immunological reagents, such as antibodies and most preferably monoclonal antibodies using standard techniques (Maino et al., 1995, Cytometry 20: 127-133).

As used herein, the terms “microarray,” “bioarray,” “biochip” and “biochip array” refer to an ordered spatial arrangement of immobilized biomolecular probes arrayed on a solid supporting substrate. Preferably, the biomolecular probes are immobilized on second linker moieties in contact with polymeric beads, wherein the polymeric beads are immobilized on first linker moieties in contact with the solid supporting substrate. Biochips, as used in the art, encompass substrates containing arrays or microarrays, preferably ordered arrays and most preferably ordered, addressable arrays, of biological molecules that comprise one member of a biological binding pair. Typically, such arrays are oligonucleotide arrays comprising a nucleotide sequence that is complementary to at least one sequence that may be or is expected to be present in a biological sample. Alternatively, and preferably, proteins, peptides or other small molecules can be arrayed in such biochips for performing, inter alia, immunological analyses (wherein the arrayed molecules are antigens) or assaying biological receptors (wherein the arrayed molecules are ligands, agonists or antagonists of said receptors). Useful microarrays for detecting differential gene expression between chemotherapeutic drug sensitive and resistant neoplastic cells are described, inter alia, in U.S. Pat. No. 6,040,138 to Lockhart et al. (commercially-available from Affymetrix, Inc., Santa Clara, Calif.) and U.S. Pat. No. 6,004,755 to Wang (commercially-available from Incyte Inc., Palo Alto, Calif.) and are also commercially available, inter alia, from Research Genetics (Huntsville, Ala.).

The practice of one embodiment of the invention is shown in FIG. 1. A tumor sample or a tumor cell line is harvested and pure cancer cell population obtained by FACS sorting using fluorescently-labeled antibodies specific for neoplastic cell markers (such as HER2, EGFR or MDR1). The sorted pure cancer cell population is then expanded by growth in cell culture to provide sufficient cells for separation into drug-sensitive and drug-resistant populations. Drug resistant cells are separated from drug sensitive cells by culture in increasing concentrations of cytotoxic drugs, and the degree of drug resistance quantitated by growing the cells in a cell proliferation-specific detectable label (such as tritiated thymidine) for a terminal portion of each cell culture experiment. IC₅₀ values can be established by performing this assay in cytophobic plates that inhibit cell attachment (and therefore prevent proliferation of non-neoplastic cells). Finally, cell culture at the IC₅₀ concentration of the cytotoxic drug in cytophobic plates is used to prepare neoplastic cells for flow sorting. It will be recognized that a significant advantage of these methods is that a mixed population of drug-sensitive and drug-resistant cells are treated simultaneously under exactly identical conditions of cell culture and drug treatment and then analyzed after separation based on their differential drug resistance characteristics.

Drug sensitive neoplastic cells are separated from drug resistant neoplastic cells, most preferably using fluorescence-activated cell sorting. Cells cultured in cytotoxic drug at the IC₅₀ are stained with a fluorescent vital stain such as propidium iodide and contacted with an apoptosis-specific, discrimination compound and with a fluorescently-labeled immunological reagent that specifically labels the apoptotic, drug sensitive neoplastic cells. In a preferred embodiment, the discrimination reagent Annexin V, which binds to phosphatidylserine exposed by apoptosis in drug sensitive cells and does not bind to drug resistant neoplastic cells. FACS analysis separates the drug resistant, living cells from cell debris, dead cells (such as stromal cells) and drug-sensitive neoplastic cells. It is also an advantage of the inventive methods that FACS sorting can discriminate between drug sensitive neoplastic cells (typically caused to be apoptotic as a result of cytotoxic drug treatment), drug resistant neoplastic cells and dead or dying cells by gating the cell sorter to perform simultaneous discrimination between these different components of the mixed population.

Cell sorting according to the methods of the invention provides sufficient numbers of separated drug-sensitive and drug-resistant neoplastic cells to be able to perform gene expression analysis. Gene expression analysis is performed to detect differences in gene expression between pure populations of neoplastic cells that are sensitive to a cytotoxic, chemotherapeutic drug and drug resistant neoplastic cells. RNA from the drug resistant neoplastic cells and drug sensitive neoplastic cells separated, most preferably, by FACS sorting is individually isolated and cDNA prepared therefrom. In preferred embodiments, the cDNA is detectably labeled, for example using radioactively-labeled or fluorescently-labeled nucleotide triphosphates. Hybridization of gene expression microarrays produces pattern of gene expression specific for cytotoxic, chemotherapeutic drug resistant neoplastic cells and neoplastic cells sensitive to the same drug and derived from the same cytotoxic drug-treated mixed cell population from which the drug-resistant cells were obtained. Identification of genes and patterns of genes differentially expressed in these cells is established by comparison of the gene expression pattern obtained by performing the microarray hybridization analysis on cDNA from neoplastic cells that are resistant to and sensitive to the cytotoxic, chemotherapeutic drug. Gene expression patterns specific for different tumor types, neoplastic cells and cytotoxic, chemotherapeutic drugs are obtained using the inventive methods.

The following Examples are intended to further illustrate certain preferred embodiments of the invention and are not limiting in nature.

EXAMPLE 1

Tumor Specimen Handling

Viable tumors samples were obtained from patients with malignant disease and placed into Oncotech transport media (complete medium, RPMI supplemented with 3% Fetal Calf Serum and antibiotics, as described below in the section Tissue Culture and Expansion) by personnel at the referring institution immediately after collection and shipped to Oncotech by overnight courier for the purpose of determining the tumors in vitro drug response profile. Upon receipt, data on tissue diagnosis, treatment history, referring physician, and patient information about the specimen was entered into a computer database. The tumor was then processed by the laboratory where three areas of the tumor are removed from the sample, fixed in Formalin, paraffin embedded, sectioned and Hematoxylin and eosin stained for pathologists' review to ensure agreement with the referring institution histological diagnosis. After in vitro drug response of the tumor specimens were determined by the laboratory, this information was sent back to the treating physician to aid in their treatment selection.

The remainder of the sample is disaggregated mechanically and processed into a cell suspension for the Extreme Drug Resistance (EDR) assay. A cytospin preparation from a single cell suspension of the tumor was examined by a technologist to determine the presence and viability of malignant cells in the specimen.

EDR Assay

The EDR assay is an agarose-based culture system, using tritiated thymidine incorporation to define in vitro drug response. This assay is predictive of clinical response (Kern et al., 1990, “Highly specific prediction of antineoplastic resistance with an in vitro assay using suprapharmacologic drug exposures,” J. Nat. Cancer Inst. 82: 582-588). Tumors were cut with scissors into pieces of 2 mm or smaller in a Petri dish containing 5 mL of complete medium. The resultant slurries were mixed with complete media containing 0.03% DNAase (2650 Kunitz units/mL) and 0.14% collagenase I (both enzymes obtained from Sigma Chemical Co., St. Louis, Mo.), placed into 50 ml Erlenmeyer flasks with stirring, and incubated for 90 min at 37° C. under a humidified 5% CO₂ atmosphere. After enzymatic dispersion into a near single cell suspension, tumor cells were filtered through nylon mesh, and washed in complete media. A portion of the cell suspension was used for cytospin slide preparation and stained with Wright-Giemsa for examination by a medical pathologist in parallel with Hematoxylin-Eosin stained tissue sections to confirm the diagnosis and to determine the tumor cell count and viability. Tumor cells were then suspended in soft agarose (0.13%) and plated at 20,000-50,000 cells per welt onto an agarose underlayer (0.4%) in 24-well plates. Tumor cells were incubated under standard culture conditions for 4 days in the presence or absence of a cytotoxic concentration of a chemotherapeutic agent. Cells were pulsed with tritiated thymidine (New Life Science Products, Boston, Mass.) at 5 μCi per well for the last 48 hours of the culture period. After labeling, cell culture plates were heated to 96° C. to liquify the agarose, and the cells are harvested with a micro-harvester (Brandel, Gaithersburg, Md.) onto glass fiber filters. The radioactivity trapped on the filters was counted with an LS-6500 scintillation Counter (Beckman, Fullerton, Calif.). Untreated cells served as a negative control. In the positive (background) control group, cells were treated with a supratoxic dose of Cisplatin (33 μM), which causes 100% cell death. Detectable radioactivity for this group was considered non-specific background related to debris trapping of tritiated thymidine on the filter. After subtracting background control values, percent control inhibition (PCI) of proliferation was determined by comparing thymidine incorporation by the treatment group with incorporation by the negative control group: PCI=100%×[1−(CPM treatment group CPM control group)]. Determinations of drug effects on tumor proliferation was performed in duplicate or triplicate. Tumor cell lines tested in the EDR assay were handled in a fashion comparable to solid tumors and plated at 1,000-5000 cells per well. Cell lines were harvested with trypsin and washed twice in phosphate buffered saline (PBS) prior to their addition to the culture plates.

Tissue Culture and Cell Expansion

All cell lines were maintained in RPMI 1640 (GibcoBRL, Grand Island, N.Y.) supplemented with 10% fetal calfserum (FCS, Gemini Bioproducts, Inc., Calabasas, Calif.), 100 IU/ml penicillin, 100 mg/ml streptomycin, and 2 mM L-glutamine (all purchased from Irvine Scientific, Irvine, Calif.) (this mixture is termed “complete medium” herein). Cells were harvested with 0.25% trypsin (GibcoBRL) after washing twice with phosphate-buffered saline (PBS, Irvine Scientific), then washed with complete medium, counted and checked for viability using trypan blue or propidium iodide (PI)-based flow cytometry, and processed for flow cytometry analysis or sorting.

In order to provide sorted tumor cells with optimal growth conditions, Becton Dickinson BIOCOAT microenvironment cell culture system was used. Tissue culture flasks (T-25, T-75, T-175, and T-225, Becton Dickinson, San Jose, Calif.) coated with rat-tail collagen I as a substrate for adhesion and growth of neoplastic cells were used in all experiments to expand sorted populations for gene array and cell sorting studies.

To approximate in vitro conditions for the growth neoplastic cells to the in vivo growth environment, Ultra Low Attachment 24-well plates (Costar, N.Y.) comprised of a covalently bound hydrogel layer that is hydrophobic and neutrally charged. This hydrogel surface inhibited non-specific immobilization of anchorage-dependent neoplastic cells via hydrophobic and ionic interactions and created an in vitro environment for culturing sorted and expanded neoplastic cells in organoid cultures. In titration experiments, the SKBR3 cell line (human breast cancer cell line, obtained from the American Type Culture Collection, Manassas, Va.) was plated in 24-well cytophobic plates at 500,000 cells per well, in duplicate, and treated with doxorubicin at concentrations of 0.02 μM, 0.04 μM, 0.08 μM, 0.17 μM, and 0.34 μM in complete medium for 5 days. As with the EDR assay described above, cells were pulsed with tritiated thymidine at 5 μCi per well for the last 48 hours of the culture period and harvested with a micro-harvester. PCI was determined by comparing thymidine incorporation by the treatment group with incorporation by the negative control group (see section “EDR Assay”). Essentially the same experimental design was utilized to evaluate doxorubicin resistance of a fresh breast carcinoma sample #80060899, using doxorubicin concentrations as follows: 0.001 μM, 0.0025 μM, 0.005 μM, 0.01 μM, 0.02 μM, 0.04 μM, 0.085 μM, and 0.17 μM.

To assess apoptotic potential of the SKBR3 cell line, SKBR3 cells at 500,000 per well were treated with doxorubicin at a pre-determined IC₅₀ (0.04 μM) and IC₉₀ (0.34 μM) concentrations for 24 and 48 hr, and analyzed by flow cytometry for Annexin V binding. In sorting experiments involving the SKBR3 cell line or sorted and expanded tumor populations, 3-5×10⁷ cells were plated in cytophobic 24-well plates at 500,000 cell per well, exposed to doxorubicin for 24 hours, collected by pipetting, washed with PBS with 1% FCS, and sorted on the basis of Annexin V binding.

Flow Cytometry Analysis and Cell Sorting

Samples of viable neoplastic cells were immediately analyzed on Becton Dickinson FACSort or FACSVantage flow cytometers equipped with a Coherent Enterprise laser tuned to 488 nm. Forward scatter, side scatter, FL-1 (FITC, fluorescein isothiocyanate), FL-2 (PE, phycoerythrin), and FL-3 (PI, propidium iodide) parameter data were collected in list mode. 10,000 events per sample were collected and consequently analyzed using the Becton Dickinson CellQuest flow cytometry acquisition software. In all samples, PI was added to exclude dead cells. Data shown are PI negative (viable) cells.

Flow sorting was performed on the Becton Dickinson FACSVantage instrument using the following parameters. In surface tumor-specific marker-based flow sorting, neoplastic cells numbers and viability were determined using the FACScan. Cells were the washed in 45 ml of serum-free RPMI and centrifuiged at 1572 g (4° C., 5 min). An aliquot (0.5-1×10⁶ cells) was labeled by the isotype control preparation (mouse IgG1 from Sigma, at a final concentration of 2 μg/mL) at 4° C. for 30 min. The remaining cells were labeled under the same conditions with the 9GG.10 anti-human HER2 monoclonal antibody (mAb) at 2 μg/mL (Neomarkers, Fremont, Calif.) or the 111.6 anti-human EGF-R mAB (Neomarkers). Cells were washed twice by ice-cold serum-free RPMI and centrifuged at 1572×g (4° C., 5 min). Washed cells were then labeled on ice with phycoerythrin (PE)-labeled anti-mouse IgG1 for 30 min, washed again in ice-cold PBS +1% FCS (1572×g, 4° C., 5 min), re-suspended in cold PBS+1% FBS supplemented with PI (1 μg/mL), and sorted on the FACSVantage. Sorted neoplastic wells were collected in a 5 mL plastic tube containing 2 mL of a 50/50 mixture of serum-free RPMI and FCS. Cell counts were recorded from the FACSVantage. After one wash with cold PBS (centrifugation at 1572×g, 4° C., 5 min), cell numbers and viabilities were determined using the FACScan. Cell pellets were used for RNA extraction if at least 2×10⁶ viable sorted HER2⁺ or EGFR⁺ cells were recovered. An additional aliquot of 5×10⁵ cells were expanded for further analysis. If less than 2.5×10⁶ viable sorted cells were recovered, all sorted cells were cultured in vitro for further analysis. Purity (defined as the percentage of neoplastic cells in the sample) and viability of the sorted populations were determined using the FACSVantage.

Flow sorting based on Annexin V binding was performed using the same protocol and FITC-labeled Annexin V (PharMingen, San Diego, Calif.), with the following modifications. The following controls were used to set up compensation and quadrants: (1) unstained cells (autofluorescence control), (2) cells stained with Annexin V-FITC only (no PI), and (3) cells stained with PI only (no Annexin V-FITC). Washed neoplastic cells were mixed with Annexin V-FITC (5 μL of the probe per 1×10⁵ cells) and/or PI (10 μL of 50 μg/mL stock solution per 1×10⁵ cells), gently vortexed and incubated at room temperature (20-25° C.) in the dark for 15 min. Annexin V-labeled cells were then re-suspended in 1×binding buffer provided by PharMingen and sorted on the FACSVantage, as recommended by the manufacturer. The following cell populations are separated: Annexin V+/PI-(sensitive cells) and Annexin V−/PI-(resistant cells). Sorted cells were collected in a FACS tubes, and purity and viability of the sorted populations were determined using the FACSVantage as described above.

SKBR3 Cells

Results of cell sorting experiments as described above with human breast carcinoma cell line SKBR3 are shown in FIGS. 2 through 6.

Cell sorting of SKBR3 cells is shown in FIGS. 2A through 2C. FIG. 2A (left) show that, even for a cultured cell line there is a wide size and shape distribution, as evidenced by the scattering in the upper right hand quadrant above the clustered scattering of the main cell mass. Staining with propidium iodide followed by sorting (FIG. 2A, right) illustrates that a certain proportion of the cells arc dead or dying and unable to exclude the fluorescent vital stain (the scattering above the line in the lower righthand quadrant. Staining with phycoerythrin-conjugated HER2 monoclonal antibody is shown in FIG. 2B. The thicker-lined scatter trace illustrates specific binding, and the thinner-lined trace illustrates non-specific binding of an antibody isotype control. Notice that there is considerable HER2 antibody-associated fluorescence (about 15%) in at intensities between 0 and 102. This indicates that HER2 expression in this cell line is heterogeneous. That these results indicate true cellular heterogeneity is shown by comparison to FIG. 2C, which is a HER2 antibody stained resort of the population represented by Ml in the graph shown in FIG. 2B. There is substantially no HER2-associated fluorescence in the range of 0 and 102, indicating that the sorted population is much more homogenous in HER2 expression than the original unsorted cell line. FIGS. 6A and 6B show that this population is maintained after returning to cell culture after sorting. FIG. 6A shows that the majority of the cells remained viable, and FIG. 6B shows that the cells bound HER2 (although a certain amount of heterogeneity can be seen to be developing in the population).

FIG. 3 shows a comparison of doxorubicin sensitivity in a HER2-sorted SKBR3 cell population such as the one shown in FIG. 2C as determined by EDR assay and cytophobic culture plate assay. Although the absolute IC₅₀ values differ, due to inherent differences in the techniques, the shape of the drug sensitivity curves are substantially parallel, indicating that cells exposed to cytotoxic drugs using the cytophobic plate assay are equivalent to cells assayed using the EDR assay. This is important because cells assayed by the EDR assay are unsuitable for RNA isolation and gene expression analyses.

SKBR3 cells treated with cytotoxic drugs were sorted after treatment with the apoptosis-discriminating agent Annexin V to separate living, drug resistant cells from apoptotic, drug sensitive cells. These results are shown in FIGS. 5A through 5D. FIG. 5A shows cell scatter of the mixed population concentrated in the lower left quadrant, indicating that the population was relatively homogenous. The results of sorting after propidium iodide staining and Annexin V treatment, followed by immunochemical staining with an FITC-conjugated anti-annexin V antibody is shown in FIG. 5B. This sort resulted in separation into living, drug-resistant neoplastic cells (R2 in the lower left quadrant), apoptotic, drug-sensitive cells (R1 in the lower right quadrant) and dying, drug-sensitive cells (in the upper right quadrant). Cell populations isolated from R1 (FIG. 5C; drug-sensitive cells) and R2 (FIG. 5D; drug-resistant cells) provides confirmation that the mixed cell population was separated into two distinct subpopulations based on binding of the fluorescently-labeled anti-Annexin V reagent.

RNA was isolated from these cell populations and analyzed. FIG. 4 is a photograph of an agarose gel electrophoretic analysis of RNA isolated from sorted, cytotoxic drug-treated cells. Lane 1 is a blank control; lane 2 is a 100 nucleotide size marker; lane 3 is RNA from doxorubicin-resistant SKBR3 cells and lane 4 is RNA from doxorubicin-sensitive SKBR3 cells, each population sorted as described. These results indicate that the RNA obtained from both drug sensitive and drug resistant cells has retained its molecular integrity (since the ribosomal RNA bands show essentially equal staining intensity.

These results demonstrate that the cell sorting methods disclosed herein are capable of providing cellular RNA from a mixed population of a tumor cell line into s separated population of drug resistance and drug sensitive cells.

Human Breast Carcinoma Tumor Sample

Results of cell sorting experiments as described above with disaggregated cells from a human breast carcinoma tumor sample are shown in FIGS. 10 through 12.

FACS sorting of disaggregated cells from a human breast carcinoma tumor sample is shown in FIGS. 10A through 10D. FACS analysis after propidium iodide staining is shown in FIG. 10A, where about 83% of the cells were viable. FIG. 10B shows negligible non-specific isotypic antibody binding after staining of the viable cells with phycoerythrin-conjugated mouse Ig2G1 antibody. FIG. 10C shows separation of the population into apoptotic, drug-sensitive neoplastic cells (R2, about 69%) and living, drug-resistant neoplastic cells (R3, about 6.5%). FIG. 10D provides confirmation that 96% of the sorted cells are viable (FIG. 10D, top) and that 97% of the sorted cells were HER2 positive (FIG. 10D, bottom).

FIGS. 11A and 11B shows HER2 antibody binding in these human breast tumor cells analyzed after cell culture following separation from non-neoplastic cells by FACS based on anti-HER antibody binding. FIG. 11A shows that 91.5% of the cells remained viable, and FIG. 11B shows that 96.2% of the cells bound HER2.

Viable neoplastic human breast carcinoma cells were separated as described above from the disaggregated tumor sample and treated with cytotoxic drugs. These cells were then sorted after treatment with the apoptosis-discriminating agent Annexin V to separate living, drug resistant cells from apoptotic, drug sensitive cells. These results are shown in FIGS. 12A through 12D. FIG. 12A shows cell scatter (99.8% in the lower left quadrant), indicating that the cells formed a relatively homogenous population in terms of cell size and shape. FIG. 12B shows separation of this population into living, drug-resistant neoplastic cells (R2; 14.6% of cells in the lower left quadrant), apoptotic, drug-sensitive cells (R1; 40.5% in the lower right quadrant) and dying, drug-sensitive cells (44.7% in the upper right quadrant). Confirmation that these cells had been sorted into distinct populations based on drug sensitivity or resistance is show in FIGS. 12C and 12D. FIG. 12C shows that apoptotic, drug-sensitive cells (93.3% of the sorted cells) resort into the lower right quadrant). FIG. 12D shows that living, drug-resistant cells (92.25% of the sorted cells) resort into the lower left quadrant).

Analysis of RNA isolated from these cell populations is shown in FIG. 4. Lane 5 shows RNA from FACS sorted doxorubicin-resistant human breast carcinoma cells, and lane 6 shows RNA from FACS sorted doxorubicin-sensitive human breast carcinoma cells, each population sorted as described. These results indicate that the RNA obtained from both drug sensitive and drug resistant cells isolated from a human breast carcinoma has retained its molecular integrity (since the ribosomal RNA bands show essentially equal staining intensity).

EXAMPLE 2 Gene Array Analyses

Cultured cells, or neoplastic cells prepared by FACS sorting as described in Example 1, were used to make mRNA for performing gene array hybridization analyses.

mRNA differential display is an effective method for isolating genes that are expressed differentially among different tissues. High-density cDNA arrays are a valuable tool for the simultaneous analysis of differential gene expression. The use of flow cytometry for the separation of pure populations of cells from complex heterogeneous tissue and high-density microarray technology provides a unique opportunity to perform high-throughput genetic analysis of pure populations of malignant cells. To demonstrate the feasibility of integrating and applying these technologies to clinical specimen, we examined the differential gene expression between pre-sorted, mixed, and post-sorted MCF7 (human breast carcinoma cells) and HUVEC (human endothelial cells) cell lines.

The gene expression profile of at least four thousand genes can be successfully generated using non-amplified RNA derived from distinct cell populations within mixed populations of cells. These results indicate that high-throughput gene expression analysis can be achieved after flow sorting for the pure population of cells and should be of value in elucidating the genetic events associated with cellular sub-populations within neoplastic tissue.

RNA Isolation

Cells were collected by gentle centrifugation (about 1500×g) to preserve their integrity. After isolating the pelleted cells from the supernatant fluid, the cells were lysed in TrIzoI® Reagent (Life Technologies™, Rockville, Md.) by repetitive pipetting, using about 1 mL of Trizol reagent per 1-10×10⁶ cells. The lysed cell sample was then incubated for 5 minutes at room temperature to permit the complete dissociation of nucleoprotein complexes. To this mixture was added about 0.2 mL chloroform per 1 mL of Trizol Reagent and the tube shaken vigorously and then incubated at room temperature for 2 minutes. The organic and aqueous phases were separated by centrifugation at about 12,000×g for 15 minutes at 5° C. The aqueous phase was carefully collected and transferred to a fresh tube, and the RNA precipitated by mixing with mixing with 0.5 mL of isopropyl alcohol. The samples were then incubated at room temperature for 10 minutes and centrifuged at 12,000×g for 10 minutes at 5° C. The supernatant was carefully removed from the RNA pellet, which was then washed once with 1 mL of 75% ethanol. The ethanol was removed and the RNA pellet air-dried for 10 minutes. Finally, the RNA pellet was dissolved in RNase-free water by incubating for 10 minutes at 55° C.

The yield and purity of total RNA was determined spectrophotometrically. The integrity of the purified RNA was determined by agarose gel electrophoresis using conventional methods.

MicroArray Assay

cDNA Probe Preparation

cDNA was prepared from cellular RNA as follows, 2.5 μg of cellular RNA was mixed with 2.0 μL Oligo dT (1 μg/μL 10-20 mer mixture) in a total volume of 10.0 μL and then placed at 70° C. for 10 minutes followed by brief chilling on ice for 2 minutes. To this mixture was added 6.0 μL 5× First Strand Buffer, 1.0μL DTT (0.1 M), 1.5 μL dNTP mixture containing dATP, dGTP, and dTTP a;plo;′/ta concentration of 20 mM, 1.5 μL Reverse Transcriptase (Superscript II, RNase H⁻, Life Technologies, Rockville, Md.) and 10 μL α(³³P)-dCTP (10 mCi/mL with a specific activity of 3000 Ci/mmol), in a total volume of 30 μL. ³³P-labeled dCTP is used because the beta-particle emission energy of this isotope is about 15% of the beta-particle energy of the more commonly-used ³³P radioisotope. This reduces the amount of “spill-over” radioactive emission between closely-spaced sites on the microarray, and makes detecting positive hybridization easier and more reliable. This reaction mixture was incubated for 90 minutes at 37° C. The reaction mixture was diluted to a final volume of 100 μL with water, and the entire volume loaded on a Bio-Spin 6 chromatography column (BioRad, Hercules, Calif.). cDNA was purified from unincorporated nucleotides following the manufacturer's instructions. The efficiency of cDNA synthesis was calculated based on the radioactivity of the probe, and was generally between 10-15%. The entire probe mixture was used for hybridization.

Hybridization

Microarrays (Known Gene Array) were obtained from Research Genetics (Huntsville, Ala).

Prior to using new membranes, the membranes were washed for at least 5 minutes with gentle agitation in a boiling (95-100° C.) solution of 0.5% SDS. The arrays were prehybridized prior to use in hybridization roller bottles containing 5 mL MicroHyb hybridization solution. Blocking reagents, including 5.0 μg human Cot-1 DNA and 5.0 μg poly dA were added to the prehybridization mixture (wherein the Cot-1 DNA is first denatured by boiling for 3 minutes). Prehybridization was performed by incubating the membrane in prehybridization buffer at 42° C. for 4 to 6 hours.

Hybridization of radiolabeled cDNA prepared as described above to the prehybridized microarrays was performed as follows. The radiolabeled cDNA probe was denatured by boiling for 3 minutes and then rapidly chilled on ice for 2 minutes. The probe was introduced into the hybridization roller bottle containing the membrane and the prehybridization mixture. The membrane was hybridized to the probe by incubation overnight (12-18 hours) at 42° C. in a hybridization roller oven at 8-10 rpm. After the hybridization reaction was complete, the membranes were washed twice with 30 mL of 2×SSC containing 1% SDS at 50° C. for 20 minutes in hybridization oven at 12-15 rpm. The membranes were then washed in 100 mL of a solution of 0.5×SSC containing 1% SDS at room temperature for 15 minutes with gentle shaking. The washed membrane was then placed on a moist filter paper and wrap it with plastic wrap.

Hybridization was detected using a using a Cyclone phosphor imaging analyzer (Packard, Meriden, Conn.) by placing the hybridized membrane adjacent to the phosphor imaging screen. The membrane was exposed to the screen for a time sufficient to detect hybridization, following the manufacturer's instructions. Results were interpreted using Pathways™ software for analysis.

After exposure and data collection, the membranes were recovered for additional rounds of hybridization by stripping the hybridized radioactive probe. This was accomplished by washing the membranes in 500 mL of boiling solution of 0.5% SDS for 1 hour with vigorous shaking. The stripped membranes were stored moist at 4° C. until use.

Hybridization experiments as described herein were performed using cDNA prepared from FACS sorted populations of drug sensitive and drug resistant SKBR3 cells and human breast carcinoma cells as described in Example 1. Results of these assays are shown in FIGS. 7, 8 and 9 and Table I for SKBR3 cells and in FIGS. 13, 14 and 15 and Table II for human breast carcinoma cells. In the SKBR3 experiments, 40 genes were found to have significantly altered levels of expression (defined as a difference greater than or equal to 1.5 fold). These genes are identified in Table I. For the human breast carcinoma cell experiments, 63 genes were found to have significantly altered levels of expression (defined as a difference greater than or equal to 1.5 fold). These genes are identified in Table II.

It should be understood that the foregoing disclosure emphasizes certain specific embodiments of the invention and that all modifications or alternatives equivalent thereto are within the spirit and scope of the invention as set forth in the appended claims.

TABLE 1 SKBR3 Anex + ve&-veSynFilComp,IR1.5.xls.xls Comparative differential gene expression analysis of SKBR3-Annexin positive (SKBR3-ANEX + ve) cells versus SKBR3-Annexin negative (SKBR3-ANEX − ve) cells revealed that 40 genes had significantly altered leveles of expression by 1.5-fold or greater. Of these 14 & 26 genes were found to be differantially expressed in the SKBR3-Annexin positive and SKBR3-Annexin negative cells, respectively. Filter Type Head1_BGAvg Head2_BGAvg Data1_RawIntensity Data2_RawIntensity GF225 SKBR3-ANNEX + ve SKBR3-ANEX − ve SKBR3-ANEX + ve SKBR3-ANEX − ve field grid col row cluster id Breast GeneFilter 13.56254 12.69236 68.75561 35.91195 1 A 6 1 Hs.11538 Breast GeneFilter 13.56254 12.69236 129.3607 77.66888 1 A 8 3 Hs.19154 Breast GeneFilter 13.56254 12.69236 151.8963 65.16193 1 B 9 18 Hs.182255 Breast GeneFilter 13.56254 12.69236 827.0767 1177.369 1 B 12 24 Hs.81234 Breast GeneFilter 13.56254 12.69236 3348.075 4251.094 1 C 8 4 Hs.214198 Breast GeneFilter 13.56254 12.69236 92.98527 134.1836 1 C 7 8 Hs.25497 Breast GeneFilter 13.56254 12.69236 66.49899 87.71584 1 C 11 26 Hs.20644 Breast GeneFilter 13.56254 12.69236 677.8284 828.687 1 C 11 30 Hs.82045 Breast GeneFilter 13.56254 12.69236 124.8971 167.9308 1 D 8 10 Hs.22405 Breast GeneFilter 13.56254 12.69236 3673.551 5320.43 1 D 4 16 Hs.77550 Breast GeneFilter 13.56254 12.69236 86.78979 125.0546 1 D 5 22 Hs.144700 Breast GeneFilter 13.56254 12.69236 48.40854 26.02505 1 E 2 22 Hs.75879 Breast GeneFilter 13.56254 12.69236 2249.312 3584.547 1 E 5 22 Hs.66576 Breast GeneFilter 13.56254 12.69236 54.74636 100.5361 1 E 8 26 Hs.24301 Breast GeneFilter 13.56254 12.69236 133.5387 81.08858 1 F 11 9 Hs.195453 Breast GeneFilter 13.56254 12.69236 91.99347 50.21226 1 F 10 10 Hs.77273 Breast GeneFilter 13.56254 12.69236 307.1604 614.9251 1 G 2 7 Hs.83422 Breast GeneFilter 13.56254 12.69236 126.5671 79.74345 1 G 5 24 Hs.2384 Breast GeneFilter 13.56254 12.69236 70.14929 127.0265 1 G 3 29 Hs.25180 Breast GeneFilter 13.56254 12.69236 166.2285 313.6372 1 G 4 30 Hs.24297 Breast GeneFilter 13.56254 12.69236 521.1713 1007.375 1 H 4 3 Hs.94672 Breast GeneFilter 13.56254 12.69236 117.3941 312.8566 1 H 3 10 Hs.100560 Breast GeneFilter 13.56254 12.69236 722.8997 561.7939 1 H 7 13 Hs.18137 Breast GeneFilter 13.56254 12.69236 536.6718 1184.14 1 H 4 23 Hs.77385 Breast GeneFilter 13.56254 12.69236 1811.95 3834.971 1 H 5 26 Hs.82646 Breast GeneFilter 13.56254 12.69236 18.33607 11.89124 2 A 11 9 Hs.9732 Breast GeneFilter 13.56254 12.69236 2597.736 3847.6 2 A 10 22 Hs.41007 Breast GeneFilter 13.56254 12.69236 72.63568 47.08278 2 B 2 27 Hs.172801 Breast GeneFilter 13.56254 12.69236 15.70985 21.11957 2 C 8 4 Hs.107325 Breast GeneFilter 13.56254 12.69236 376.6325 497.4136 2 C 9 20 Hs.25600 Breast GeneFilter 13.56254 12.69236 1411.844 1994.42 2 C 2 23 Hs.155979 Breast GeneFilter 13.56254 12.69236 67.77326 104.8175 2 D 2 8 Hs.138671 Breast GeneFilter 13.56254 12.69236 62.43242 38.44348 2 D 12 21 Hs.196914 Breast GeneFilter 13.56254 12.69236 208.0544 112.4615 2 E 2 8 Hs.113368 Breast GeneFilter 13.56254 12.69236 330.6748 184.9721 2 E 3 17 Hs.172153 Breast GeneFilter 13.56254 12.69236 122.224 188.4318 2 E 9 29 Hs.7489 Breast GeneFilter 13.56254 12.69236 16.32129 11.35158 2 G 12 30 Hs.184967 Breast GeneFilter 13.56254 12.69236 384.1351 682.7194 2 H 8 8 Hs.31396 Breast GeneFilter 13.56254 12.69236 285.0607 565.8192 2 H 6 13 Hs.53656 Breast GeneFilter 13.56254 12.69236 78.09672 130.7549 2 H 3 18 Hs.159860 Filter Type NormInt1 NormInt2 GF225 title gene SKBR3-ANEX + ve SKBR3-ANEX − ve Ratio Diff Breast GeneFilter APR213 protein complex subunit p41 ARC41 1966.871 999.9936 1.9868834 986.88 Breast GeneFilter KRAB-associated protein 1 TIF1B 3738.21 2162.745 1.72845626 1575.47 Breast GeneFilter non-histone chromosome protein 2 (S. NHP2L1 5632.062 2761.361 2.03959608 2870.7 Breast GeneFilter immunoglobulin superfamily, member 3 IGSF3 30666.62 49893.25 −1.62695646 −19226.6 Breast GeneFilter Human mRNA for pM5 protein — 124362.2 196881.8 −1.58313277 −72519.6 Breast GeneFilter MAX binding protein MNT 3453.881 6214.475 −1.79927301 −2760.59 Breast GeneFilter branched chain alpha-ketoacid BCKDK 2470.064 4062.402 −1.64465415 −1592.34 Breast GeneFilter midkine (neurite growth-promoting factor 2) MDK 25177.52 38379.16 −1.52434206 −13201.6 Breast GeneFilter leukocyte immunoglobulin-like receptor MR-10 4440.301 7265.941 −1.63636231 −2825.64 Breast GeneFilter CDC28 protein kinase 1 CKS1 130600.9 205703 −1.57505095 −75102.1 Breast GeneFilter ephrin-B1 EFN81 3085.522 4834.966 −1.56698489 −1749.44 Breast GeneFilter ribsomal protein L19 RPL19 1647.476 848.8703 1.94078612 798.61 Breast GeneFilter Human MDA-7 (mda-7) mRNA, complete cds — 76550.27 116918.7 −1.52734542 −40368.4 Breast GeneFilter polymerase (RNA) II (DNA directed) POLR2E 1863.169 3279.23 −1.760028 −1416.06 Breast GeneFilter ribosomal protein 527 (metallopanstimulin 1) RP527 4267.264 2690.311 1.71887368 1936.95 Breast GeneFilter ras homolog gene family, member A ARHA 3187.677 1665.914 1.91347051 1521.76 Breast GeneFilter H. sapiens MLN51 mRNA — 11694.91 20600.61 −1.76150262 −8905.7 Breast GeneFilter tumor protein D52 TPD52 4818.948 2671.486 1.80384541 2147.46 Breast GeneFilter purine-rich element binding protein A PURA 2670.883 4255.516 −1.59329927 −1584.63 Breast GeneFilter multiple endocrine neoplasia 1 MEN1 6329.027 10513.86 −1.66121292 −4184.83 Breast GeneFilter GCN5 (general control of amino-acid GCN5L1 16570 26199.65 −1.58115005 −9.629.65 synthesis, yeast, homolog-like 1 Breast GeneFilter Human mRNA for KIAA0276 gene, partial cds — 3732.4 8136.724 −2.18002462 −4404.32 Breast GeneFilter laminin receptor 1 (67 kD); Ribsomal protein LAMR1 22983.7 14350.97 1.60154343 8632.73 Breast GeneFilter Human non-muscle myosin alkali light chain — 17062.81 30796.93 −1.80491519 −13734.1 mRNA, 3′ end Breast GeneFilter heat shock, 40 kD protein 1 HSPF1 57608.71 99739.32 −1.73132372 −42130.6 Breast GeneFilter ESTs, Weakly similar to !!!! ALU SUBFAMILY — 426.0522 282.9269 1.50587392 143.13 J WARNING ENTRY !!!! (H. sapiens) Breast GeneFilter ESTs, Weakly similar to (define not available — 60360.32 91545.48 −1.51664996 −31185.2 3880489) (C. elegans) Breast GeneFilter isoleucine-tRNA synthetase IARS 2876.156 1777.693 1.61791492 1096.46 Breast GeneFilter ESTs — 577.6293 893.7206 −1.54722166 −316.09 Breast GeneFilter ESTs — 13848.25 21049.14 −1.51998568 −7200.69 Breast GeneFilter Human mRNA for KIAA0295 gene, partial cds — 51911.51 84398.23 −1.62580955 −32486.7 Breast GeneFilter fms-related tyronsine kinase 1 (vascular FLT1 2493.025 3850.02 −1.54431641 −1356.99 endothelial growth factor/vascular permeability Breast GeneFilter ESTs — 2296.563 1412.056 1.62639689 884.51 Breast GeneFilter guanine nucleotide binding protein (G protein), GNAS1 7321.198 3936.93 1.85962093 3384.27 alpha stimulating activity polypeptide 1 Breast GeneFilter glutathione peroxidase 3 (plasma) GPX3 11643.11 6475.298 1.79808021 5167.81 Breast GeneFilter ESTs — 4300.923 6596.413 −1.53372014 −2295.49 Breast GeneFilter ESTs — 663.6732 424.2502 1.56434357 239.42 Breast GeneFilter ESTs — 13675.62 23745.72 −1.73632944 −10069.9 Breast GeneFilter ESTs — 10148.61 19679.81 −1.93916249 −9531.2 Breast GeneFilter ESTs — 2780.366 4547.796 −1.63568234 −1767.43

TABLE 2 #80060899BREANEX + ve&-veSynFilComp.IR1.5xls Comparative differential gene expression analysis of #80060899BRE-Annexin positive (#80060899BRE-ANEX + ve) cells versus #800608998BRE-Annexin negative (#80060899BRE-ANEX − ve) cells revealed that 63 genes had significantly altered leveles of expression by 1.5-fold or greater. All of these genes were found to be differentially expressed in the #80060899BRE-Annexin positive cells Head1_BGAvg Head2_BGAvg Data1_RawIntensity Data2_RawIntensity Filter Type #80060899BRE #80060899BRE #80060899BRE- #80060899BRE- Table Name GF225 ANEX + ve ANEX − ve ANEX + ve ANEX − ve field grid col row GF225 Breast GeneFilter 12.16622 12.89396 702.05 488.1645 1 A 6 4 GF225 Breast GeneFilter 12.16622 12.89396 1011.696 636.6229 1 A 7 5 GF225 Breast GeneFilter 12.16622 12.89396 265.7989 133.0044 1 A 11 6 GF225 Breast GeneFilter 12.16622 12.89396 98.7685 75.77792 1 A 6 8 GF225 Breast GeneFilter 12.16622 12.89396 543.7198 330.2836 1 A 8 11 GF225 Breast GeneFilter 12.16622 12.89396 146.1391 114.645 1 A 7 12 GF225 Breast GeneFilter 12.16622 12.89396 76.26098 55.45963 1 A 9 17 GF225 Breast GeneFilter 12.16622 12.89396 421.2297 345.7194 1 A 11 17 GF225 Breast GeneFilter 12.16622 12.89396 236.2751 167.1667 1 A 12 19 GF225 Breast GeneFilter 12.16622 12.89396 257.5699 186.8602 1 A 12 25 GF225 Breast GeneFilter 12.16622 12.89396 3749.604 2892.917 1 A 8 29 GF225 Breast GeneFilter 12.16622 12.89396 201.3526 126.1709 1 A 5 30 GF225 Breast GeneFilter 12.16622 12.89396 1022.082 730.9009 1 A 7 30 GF225 Breast GeneFilter 12.16622 12.89396 217.6139 115.498 1 C 9 2 GF225 Breast GeneFilter 12.16622 12.89396 2595.324 1575.159 1 C 8 4 GF225 Breast GeneFilter 12.16622 12.89396 109.9706 86.00154 1 C 5 14 GF225 Breast GeneFilter 12.16622 12.89396 156.5895 116.531 1 C 3 25 GF225 Breast GeneFilter 12.16622 12.89396 1730.067 1305.118 1 D 9 3 GF225 Breast GeneFilter 12.16622 12.89396 937.867 672.9494 1 D 5 9 GF225 Breast GeneFilter 12.16622 12.89396 141.4012 114.6111 1 F 7 7 GF225 Breast GeneFilter 12.16622 12.89396 614.5146 513.2037 1 F 6 21 GF225 Breast GeneFilter 12.16622 12.89396 174.0228 128.9007 1 F 2 29 GF225 Breast GeneFilter 12.16622 12.89396 1173.544 976.9803 1 G 7 14 GF225 Breast GeneFilter 12.16622 12.89396 105.6052 78.61996 1 G 8 29 GF225 Breast GeneFilter 12.16622 12.89396 106.472 80.64673 1 H 6 4 GF225 Breast GeneFilter 12.16622 12.89396 416.1731 302.3279 1 H 10 5 GF225 Breast GeneFilter 12.16622 12.89396 74.64893 56.23211 1 H 11 6 GF225 Breast GeneFilter 12.16622 12.89396 32.11365 21.7196 1 H 11 9 GF225 Breast GeneFilter 12.16622 12.89396 1940.258 1276.052 1 H 12 10 GF225 Breast GeneFilter 12.16622 12.89396 229.0105 181.325 1 H 12 11 GF225 Breast GeneFilter 12.16622 12.89396 658.1039 504.0877 1 H 12 13 GF225 Breast GeneFilter 12.16622 12.89396 157.5227 133.8199 1 H 8 18 GF225 Breast GeneFilter 12.16622 12.89396 243.0308 216.6431 1 H 2 21 GF225 Breast GeneFilter 12.16622 12.89396 589.0263 520.9788 1 H 12 22 GF225 Breast GeneFilter 12.16622 12.89396 574.3094 512.2259 1 H 4 23 GF225 Breast GeneFilter 12.16622 12.89396 397.9135 332.7921 1 H 12 24 GF225 Breast GeneFilter 12.16622 12.89396 432.522 347.6953 1 H 12 25 GF225 Breast GeneFilter 12.16622 12.89396 1276.832 1120.96 1 H 12 28 GF225 Breast GeneFilter 12.16622 12.89396 2904.885 2262.511 2 A 8 5 GF225 Breast GeneFilter 12.16622 12.89396 494.9388 380.2501 2 A 2 8 GF225 Breast GeneFilter 12.16622 12.89396 110.3552 71.43282 2 A 7 9 GF225 Breast GeneFilter 12.16622 12.89396 103.4821 59.63686 2 A 12 10 GF225 Breast GeneFilter 12.16622 12.89396 2432.994 1890.604 2 A 8 13 GF225 Breast GeneFilter 12.16622 12.89396 748.2268 469.9998 2 A 2 14 GF225 Breast GeneFilter 12.16622 12.89396 838.4484 590.2916 2 A 9 17 GF225 Breast GeneFilter 12.16622 12.89396 3341.728 2201.421 2 A 10 22 GF225 Breast GeneFilter 12.16622 12.89396 178.9771 100.5989 2 A 12 22 GF225 Breast GeneFilter 12.16622 12.89396 121.6087 95.55091 2 A 10 28 GF225 Breast GeneFilter 12.16622 12.89396 1549.878 1144.886 2 B 10 16 GF225 Breast GeneFilter 12.16622 12.89396 189.649 138.4131 2 B 4 22 GF225 Breast GeneFilter 12.16622 12.89396 306.0685 255.746 2 C 10 14 GF225 Breast GeneFilter 12.16622 12.89396 116.2641 84.69499 2 C 12 27 GF225 Breast GeneFilter 12.16622 12.89396 365.4977 290.1935 2 D 7 27 GF225 Breast GeneFilter 12.16622 12.89396 2048.506 1694.005 2 B 6 20 GF225 Breast GeneFilter 12.16622 12.89396 485.7777 400.9786 2 E 9 27 GF225 Breast GeneFilter 12.16622 12.89396 679.442 554.5363 2 G 4 7 GF225 Breast GeneFilter 12.16622 12.89396 1038.763 809.8124 2 G 7 9 GF225 Breast GeneFilter 12.16622 12.89396 437.1326 317.3184 2 G 3 10 GF225 Breast GeneFilter 12.16622 12.89396 352.3212 196.1996 2 G 6 13 GF225 Breast GeneFilter 12.16622 12.89396 34.98531 25.10817 2 H 8 3 GF225 Breast GeneFilter 12.16622 12.89396 157.6186 103.6439 2 H 4 11 GF225 Breast GeneFilter 12.16622 12.89396 386.0974 248.6657 2 H 6 13 GF225 Breast GeneFilter 12.16622 12.89396 315.2936 175.1065 2 H 6 25 NormInt1 NormInt2 #80060899BRE #80060899BRE- Table Name cluster id title gene ANEX + ve ANEX − ve Ratio Diff GF225 Hs.80475 polymerase (RNA) II (DNA directed) POLR2J 29258.06 16347.19 1.789791 12910.9 GF225 Hs.8765 Homo sapiens RNA helicase-related protein — 42162.63 21318.63 1.977736 20844 GF225 Hs.75415 beta-2-microglobulin B2M 11077.21 4453.925 2.487068 6623.29 GF225 Hs.115617 corticotropin releasing hormone-binding CRHBP 4116.95 2537.58 1.622095 1578.62 GF225 Hs.14839 polymerase (RNA) II (DNA directed) POLR2G 22659.62 11060.23 2.048748 11599.4 GF225 Hs.16232 connector enhancer of KSR-like (Drosophia CNK1 6090.372 3839.125 1.586396 2251.25 kinase supproessor of ras) GF225 Hs.79339 lectin, galactoside-binding, soluble, 3 binding LGALS3BP 3178.19 1857.18 1.711299 1321.01 protein (galectin 6 binding protein) GF225 Hs.119387 KIAA0792 gene product KIAA0792 17544.82 11577.13 1.516337 5977.7 GF225 Hs.112183 mulS (E. coli) homolog 5 MSH5 9846.806 5597.921 1.759011 4248.88 GF225 Hs.180780 Homo sapiens agrin precursor mRNA, partial — 10734.27 6257.397 1.715453 4476.88 GF225 Hs.75841 Homo sapiens mRNA for ERp28 protein — 156265.4 96875.27 1.613058 59390.2 GF225 Hs.808 heterogeneous nuclear ribonucleoprotein F HNRPF 8391.408 4225.091 1.986089 4166.32 GF225 Hs.184601 solute carrier family 7 (cationic amino acid) SLC7A5 42695.46 24475.72 1.740315 18119.7 transporter.y+system), member 5 GF225 Hs.203502 secretory leukocyte protease inhibitor SLPI 14072.85 6415.639 2.193523 7657.22 GF225 Hs.214198 Human mRNA for pM5 protein — 167836.8 86745.27 1.934824 81091.5 GF225 Hs.11465 glutathione-S-transferase like GSTTLp28 7111.677 4736.173 1.501566 2375.5 GF225 Hs.78068 carboxypeptidase Z CPZ 10125.18 6362.385 1.591413 3762.79 GF225 Hs.179661 Homo sapiens clone 24703 beta-tubulin — 92636.98 61654.04 1.502529 30982.9 GF225 Hs.170008 methylmalonate-semialdehyde MMSDH 50218.4 31790.26 1.579679 18428.1 GF225 Hs.83363 Human nested gene protein gene, complete — 7019.64 4500.866 1.55962  2518.77 GF225 Hs.84084 amyloid beta precursor protein (cytoplasmic APPBP2 30506.6 20153.9 1.513682 10352.7 GF225 Hs.214197 plasmidogen activator, tissue PLAT 8639.085 5062.028 1.706645 3577.06 GF225 Hs.75742 matrix Gla protein MGP 59679.07 39540.87 1.509301 20138.2 GF225 Hs.180347 carcinoembryonic antigen CEA 5370.416 3181.949 1.687775 2188.47 GF225 Hs.135084 cystatin C (amyloid angiopathy and cerebral CST3 5174.043 2898.465 1.785098 2275.58 GF225 Hs.146688 microsomal glutathione S-transferase 1-like 1 MGST1L1 20224.07 10865.62 1.86129  9358.45 GF225 Hs.119251 ubiquinol-cytochrome c reductase core UQCRC1 3627.59 2020.974 1.794971 1606.62 GF225 Hs.26002 LIM domain binding 1 LDB1 1560.573 780.5994 1.999199 779.97 GF225 Hs.5372 claudin 4 CLDN4 94287.46 45861.14 2.055933 48426.3 GF225 Hs.154737 Homo sapiens serine protease mRNA, — 1128.84 6516.796 1.707716 4612.04 GF225 Hs.108809 chaperonin containing TCP1, subunit 7 (eta) CCT7 31980.78 18116.84 1.765251 13863.9 GF225 Hs.83919 Glucosidase I GCS1 7654.867 4809.47 1.591624 2845.4 GF225 Hs.204238 Lipocalin 2 (oncogene 24p3) LCN2 11810.16 7786.123 1.516822 4024.04 GF225 Hs.10326 Homo sapiens mRNA for Epsilon COP — 28623.93 18723.91 1.528737 9900.02 GF225 Hs.77385 Human non-muscle myosin alkali light chain — 27906.75 18409.33 1.516012 9499.43 GF225 Hs.102824 tropomyosin 4 TMP4 19336.74 11960.5 1.616716 7376.24 GF225 Hs.82109 syndecan 1 SDC1 21018.55 12496.12 1.682006 8522.43 GF225 Hs.6396 Homo sapiens hJTB mRNA, complete cds — 62048.07 40287.14 1.540146 21760.9 GF225 Hs.97176 ESTs — 101850.6 63786.51 1.596742 38064.1 GF225 Hs.181165 eukaryotic translation elongation factor 1 EEF1A1 17353.46 10720.32 1.618746 6633.15 GF225 Hs.112242 ESTs — 3869.256 2013.891 1.921283 1855.36 GF225 Hs.40780 ESTs — 3628.273 1681.33 2.157978 1946.94 GF225 Hs.169388 ESTs — 85305.26 53301.41 1.600432 32003.9 GF225 Hs.74562 Human siah binding protein 1 (SiahBP1) — 26234.21 13250.61 1.979849 12983.6 GF225 Hs.165743 ESTs, Highly similar to (define not available) — 29397.54 16641.97 1.76647  12755.6 GF225 Hs.41007 ESTs, Weakly similar to (define not available — 117167.1 62064.23 1.887837 55102.9 3880849) (C. elegans) GF225 Hs.72132 ESTs — 6275.266 2836.166 2.212588 3439.1 GF225 Hs.97272 ESTs — 4263.826 2693.848 1.582801 1569.98 GF225 Hs.32360 ESTs, Weakly similar to KIAA0454 protein — 75336.98 50123.38 1.503031 25213.6 GF225 Hs.206654 ESTs, Moderately similar to !!!! ALU — 9218.518 6059.759 1.521268 3158.76 SUBFAMILY SQ WARNING ENTRY!!!! GF225 Hs.8135 ESTs — 17991.39 11934.77 1.507477 6056.62 GF225 Hs.159986 ESTs — 6834.264 3952.42 1.729134 2881.84 GF225 Hs.183211 ESTs, Weakly similar to collagen — 18792.14 11868.46 1.583367 6923.68 GF225 Hs.103938 ESTs — 99663.57 66037.28 1.509202 33626.3 GF225 Hs.11747 ESTs — 23633.98 15631.32 1.511963 8002.66 GF225 Hs.140978 ESTs — 35519.65 22940.63 1.548329 12579 GF225 Hs.10098 ESTs, Weakly Similar to RCK (H. sapiens) — 54304.11 33501.16 1.620962 20803 GF225 Hs.93557 proenkephalin PENK 22852.28 13127.16 1.74084  9725.12 GF225 Hs.45109 ESTs — 18418.54 8116.587 2.269246 10302 GF225 Hs.106255 ESTs, Highly similar to MEM3 (M. musculus) — 1563.57 971.0319 1.610215 592.54 GF225 Hs.146059 ESTs — 7044.317 4008.319 1.757424 3036 GF225 Hs.53656 ESTs — 17255.54 9616.882 1.794297 7638.66 GF225 Hs.111968 ESTs — 14091.16 6772.059 2.080779 7319.1 

1. A method for detecting a gene expression profile of living neoplastic cells that are resistant to a cytotoxic compound and distinguishing said profile from the gene expression profile of living neoplastic cells that are sensitive to the cytotoxic compound in a mixed population of cells from a tumor sample, the method comprising the steps of: a) contacting the mixed population of cells with the cytotoxic compound for a time and at a concentration wherein the neoplastic cells that are sensitive to the cytotoxic compound undergo apoptosis; b) contacting the mixed population of step (a) with a vital stain or fluorescent dye; c) contacting the mixed population of cells of step (b) with a discrimination compound that binds to phosphatidylserine; d) contacting the mixed cell population of step (c) with a detectably-labeled immunological reagent that specifically binds to the phosphatidylserine discrimination compound; and e) separating the cells in the mixed population of step (d) that are not stained with the vital stain from the cells that are stained with the vital stain; f) separating and isolating the cells in the mixed population of step (e) that are not stained with the vital stain and that do not bind the immunological reagent from the cells in the mixed population of step (e) that are not stained with the vital stain and that do bind the immunological reagent; g) isolating cellular RNA from the each of the separated cells selected in step (f); h) preparing detectably-labeled cDNA from the cellular RNA isolated in step (g); i) hybridizing each of the cDNA preparations prepared in step (h) to a gene array comprising at least 4000 eukaryotic genes; j) detecting a pattern of gene expression for hybridization of each of the cDNA preparations prepared from the mRNA isolated from the cells selected in step (f); and k) comparing the pattern of gene expression detected in step (j) from hybridization of the microarray with cDNA from cells that are not stained with the vital stain and that do not bind the immunological reagent with a pattern of gene expression obtained by hybridizing cDNA prepared from cells that are not stained with the vital stain and that do bind the immunological reagent.
 2. The method of claim 1, wherein the vital stain is propidium iodide.
 3. The method of claim 1, wherein the cells of step (f) are separated by fluorescence-activated cell sorting.
 4. The method of claim 1, wherein the cytotoxic compound is a chemotherapeutic drug.
 5. The method of claim 1, wherein the cDNA is detectably labeled with a fluorescent label.
 6. The method of claim 1, wherein the mixed population is contacted with the cytotoxic compound under in vitro cell culture conditions whereby the cells cannot attach to a solid substrate.
 7. The method of claim 1, wherein the tumor sample is a solid tumor sample and the mixed cell population is a disaggregated tumor sample.
 8. The method of claim 1, wherein the tumor sample is a hematopoietic tumor sample and the mixed cell population a nucleated hematopoietic cell sample. 